Texas Data Repository Harvested Dataverse provides code and supporting data for research on automated detection of instability-inducing channel geometry transitions in Saint-Venant simulations of large-scale river networks. The data was authored by Yu, Cheng-Wei and was last updated on March 18, 2024. The associated manuscript is in preparation for peer review.
Use Cases
- Training or testing instability detection algorithms based on channel geometry transition data.
- Benchmarking Saint-Venant equation solvers against known instability-inducing conditions.
- Analyzing the relationship between channel geometry changes and simulation stability in river networks.
Strengths
- Data is directly linked to a specific, described research problem in computational hydrology.
- Last update timestamp of 2024-03-18 suggests recent activity and potential relevance.
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count and file formats are unknown, which may limit suitability assessment.
Provenance
- Source
- Texas Data Repository Harvested Dataverse
- Collection Method
- Likely generated as supporting material for a computational hydrology research project.
- Time Range
- null
- Freshness
- Last updated 2024-03-18 07:52:54
- Geography
- null